Ultrafast, accurate, and robust localization of anisotropic dipoles.
10.1007/s13238-013-3904-1
- Author:
Yongdeng ZHANG
1
;
Lusheng GU
;
Hao CHANG
;
Wei JI
;
Yan CHEN
;
Mingshu ZHANG
;
Lu YANG
;
Bei LIU
;
Liangyi CHEN
;
Tao XU
Author Information
1. College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
- Publication Type:Journal Article
- MeSH:
Alcohol Oxidoreductases;
analysis;
genetics;
metabolism;
Algorithms;
Animals;
COS Cells;
Cercopithecus aethiops;
Cytochrome P-450 Enzyme System;
analysis;
genetics;
metabolism;
HeLa Cells;
Humans;
Imaging, Three-Dimensional;
Microscopy, Fluorescence;
Normal Distribution;
Plasmids;
metabolism
- From:
Protein & Cell
2013;4(8):598-606
- CountryChina
- Language:English
-
Abstract:
The resolution of single molecule localization imaging techniques largely depends on the precision of localization algorithms. However, the commonly used Gaussian function is not appropriate for anisotropic dipoles because it is not the true point spread function. We derived the theoretical point spread function of tilted dipoles with restricted mobility and developed an algorithm based on an artificial neural network for estimating the localization, orientation and mobility of individual dipoles. Compared with fitting-based methods, our algorithm demonstrated ultrafast speed and higher accuracy, reduced sensitivity to defocusing, strong robustness and adaptability, making it an optimal choice for both two-dimensional and three-dimensional super-resolution imaging analysis.
